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GC/MS and proteomics to unravel the painting history of the lost Giant Buddhas of Bāmiyān (Afghanistan).
- Source :
-
PloS one [PLoS One] 2017 Apr 05; Vol. 12 (4), pp. e0172990. Date of Electronic Publication: 2017 Apr 05 (Print Publication: 2017). - Publication Year :
- 2017
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Abstract
- A chemical investigation of the organic paint binders of the Giant Buddhas of Bāmiyān was performed using an analytical approach based on mass spectrometry, combining traditional gas chromatography/mass spectrometry protocols with advanced proteomics methodologies. The research was carried out on a selection of rescued fragments. The data revealed the use of egg proteins as the paint binders of the original layers, in accordance with the traditional use of this proteinaceous medium in antiquity, spanning from the Mediterranean basin to the Far East, and already in the Bronze Age. Egg tempera was thus known to artists of the region in the first centuries AD, probably also due to the position of the Bāmiyān valley, which was connected to the Silk Road. Milk was found in the first historical overpaintings. A new proteomics approach was used, which was able to identify the source of the milk proteins present in the restoration layers, despite their age and degradation. In particular cow's and goat's milk were both found, in agreement with the documented presence of rich pastures in the Bāmiyān valley when the historical restorations were carried out. Investigating the materials of the Giant Buddhas not only enabled us to obtain isolated data on these invaluable works of art, which are now lost, but contributes to understanding the big "puzzle" of our past and the development of our culture, by implementing and supporting written sources, stylistic and anthropological studies with molecular data.
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 12
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 28379960
- Full Text :
- https://doi.org/10.1371/journal.pone.0172990